During use of a social network, a user receives target information recommended by a server, and the target information may be an advertisement, news or a video.
Interaction operations such as commenting, liking, and forwarding by friends of the user on the target information affect a click-through rate of the user on the target information. Therefore, to improve a click-through rate of the target information, when receiving a request to obtain information sent by the user by using a client, the server needs to calculate influence forces of all friends of the user on each candidate target information, and recommend candidate target information whose influence force is relatively large as finally recommended target information to the user. For example, when the user possess n friends and the server performs screening to select m pieces of candidate target information in advance, the n friends may perform t types of interaction operations on each candidate target information. When receiving a request to obtain information sent by the user by using a client, the server may obtain influence forces of all the friends on each candidate target information only through m×n×t numbers of calculation. The term client may refer to a client terminal or a client application on a terminal device, or the like.
During implementation of the present invention, the inventor finds that the foregoing technology at least has the following problems:
Generally, a quantity of friends of a user (n) is relatively large. Based on the foregoing processing manner, when the user sends a request to obtain information to a server by using a client, the server needs to perform calculation whose complexity is relatively high. Consequently, the client can obtain a feedback of the server only after a relatively long time.